Solid-state arrays have moved the external controller-based storage array market from a relatively stagnant incrementally improving market with slow-changing dynamics to a progressive neoclassical market. Improvements in the dynamics of many factors—such as reduced storage administration, power, cooling, rack space, increased performance and density—have changed the accepted assumptions of the previous SAN storage array market. More vendors design and develop their own custom solid-state solutions. Consequently, more vendors are offering alternate solid-state media form factors with denser and faster systems when they create their own NAND flash storage packaging. From a whole system perspective, the largest SSAs now scale to 3.9 PB, and next-generation SSD technology and interconnects will again redefine performance capabilities, creating demand for faster storage networks.
Neither the solid-state array, nor the storage array administrator is the bottleneck anymore; but network latency has become the challenge. This has extended the requirement and life span for 16 Gbps and 32 Gbps Fibre Channel SANs, as Ethernet-based networks and related storage protocols struggle to keep up. Many new vendors have entered the market who provide comprehensive service management, and along with many traditional storage vendors, they continue to transition their portfolios from HDD-based arrays to all solid-state arrays.
Therefore, an SSA that is two to three times more expensive to purchase becomes a cost-effective replacement for a hybrid or general-purpose array at increased utilization rates. With regard to performance, one SSD can typically replace multiple HDDs, combined with data reduction features and increased storage administrator productivity the price point at which SSA investment decisions are made is dropping rapidly. Redundant array of independent disks (RAID) rebuild times for high-capacity SSDs are also faster than for high-capacity HDDs. Therefore, as HDD storage capacities increase, so do HDD recovery times, and SSAs reduce the risk exposure during any media failure and recovery window. Use cases for SSAs are moving into analytics, file and object workloads, and some customers even use SSAs as backup targets to reduce backup and restore windows.
Price and ownership programs translate into very competitive purchase prices for buyers, but vendors are faced with challenges to becoming profitable as incumbent vendors discount to avoid losing market share and new vendors discount to attract new customers. Because the SSA market has expanded rapidly with SSD reliability being equal to or better than HDD arrays, and feature parity also equalizing, the competitive battle to differentiate has moved to ease of ownership, and remote and pre-emptive support capabilities.
The typical approach to providing a high performance digital storage system has been to include high RPM (revolutions per minute) drives and to increase the number of drives available to distribute the memory storage load. However, this approach has increased the initial system cost to acquire a large number of expensive disks and has also increased ongoing costs to power and cool these disks. Metadata, or data describing data, has therefore been utilized to compress data and to avoid storage of duplicate copies of compressed data by storing the location of duplicate copies in memory.
In current hard drive and solid state memory hybrid configurations, the SSD (solid state drive) drives are statically and physically partitioned into 3 sets—each representing their use cases—Log (write cache), L2 cache (read cache), and metadata. This division has been primarily driven by the capacity sizing and is not in sync with the performance requirements of IOPS (Instructions Operations per second) and/or bandwidth (BW).
This creates imbalance in the life-cycle of the SSD uses and is not a very efficient utilization of the performance capacity available from SSD devices. Most of the time, the usage is bi-modal, and, hence, it effectively wastes the performance available from the underlying devices. The usage of metadata, for example, is pretty pronounced in second phase of spa_sync (Storage Pool Allocator synchronize), for rest of the time, the metadata usage is pretty quiet. The bi-modal behavior can be driven by the application as well. For example, typical new data write workloads stress on log (write) and cache (read) and much less on metadata whereas metadata oriented workloads stress more on metadata IOPS with much less stress on log and cache. Hence, the SSD devices are not being used optimally when they are physically partitioned.
The problem is not only evident in performance and under-utilization, even the SSD usage is quite in-efficient. When the pool does not have too much metadata, the physically partition is effectively wasting the space which could be consumed by the cache (read) to provide higher performance. As the metadata usage grows, the cache (read) space can make way to the metadata space, providing flexibility.
In traditional storage systems, metadata is stored on the disk itself. When data is being written or read from disk, the storage system has to write or read the metadata as well. This adds to the overhead of the overall write or read operation in terms of access time and latency as well as to hardware costs. There is therefore a long felt need for a block and file storage system with accelerated metadata management capable of scaling to larger disk storage.